John McCalmont

Development of a Sense and Avoid System

Remotely Operated Aircraft (ROAs) currently do not have convenient access to civil airspace due to their inability to provide an onboard capability to “see and avoid” air traffic. Defense Research Associates, Inc. and AFRL/SNJT have developed affordable technology based on silicon charge couple device sensors and passive moving target detection algorithms. Previously, a flight demonstration proved real-time implementation of complex detection and tracking algorithms with multiple sensors providing a wide field of regard was feasible. This paper documents lessons learned from that demonstration, subsequent improvements made to the prototype system, resulting performance improvements, and planned next steps .

Test and Integration of a Detect and Avoid System

Remotely Operated Aircraft (ROAs) currently do not have convenient access to civil airspace due to their inability to provide an onboard capability to “see and avoid” air traffic. Defense Research Associates, Inc. and AFRL/SNJT have developed affordable technology based on silicon charge couple device sensors and passive moving target detection algorithms. Previously, an all-software implementation of the algorithms demonstrated concept feasibility by using video data recorded during flight testing. This paper documents subsequent implementation and field testing of a real-time version of the system with field programmable gate arrays handling the detection processing and multiple sensors to demonstrate the wide field of regard required. The implementation met demonstration goals by functioning reliably in real-time and providing detection and false detection performance comparable to that of the previous, non-real-time version.

SENSE AND AVOID, PHASE I (MAN-IN-THE-LOOP) ADVANDED TECHNOLOGY DEMONSTRATION

The Sensors Directorate of the Air Force Research Laboratory (AFRL), in conjunction with the Global Hawk Systems Group, the J-UCAS System Program Office and contractor Defense Research Associates, Inc. (DRA) is conducting an Advanced Technology Demonstration (ATD) of a sense-and-void capabi lity with the potential to satisfy the Federal Aviation Administration’s (FAA) requirement for Unmanned Aerial Vehicles (UAV) to provide “an equivalent level of safety, comparable to see -and-avoid requirements for manned aircraft”. This FAA requirement must be satisfied for UAV operations within the national airspace. The Sense-and-Avoid, Phase I (Man -in-the-Loop) ATD will demonstrate an on -board, wide field of regard, multisensor visible imaging system operating in real time and capable of passively detecting approaching aircraft, declaring potential collision threats in a timely manner and alerting the human pilot located in the remote ground control station. The technology basis, program schedule, and transition plans of the ATD will be presented. I. INTODUCTION Federal Aviation Administration (FAA) Regulation 7610.4 states remotely operated aircraft (ROA, aka UAV, UAS) must provide an “…equivalent level of safety, comparable to see -and-avoid requirements for manned aircraft” in order to operate in the National Air Space (NAS). The capability must be effective against all air traffic, with or without active, transponder-based collision avoidance systems. Currently, no ROA “see and avoid” capability exists. ROAs operating in the NAS must obtain Certificates of Authorization, a cumbersome , time consuming process, and/or use either chase planes or ground-based observers. The Air Force Research Laboratory’ Sensors Directorate (AFRL/SN), the Aeronautical System Center (ASC) and Defense Research Associates, Inc. (DRA) have developed sense and avoid technology that has the potential to meet the FAA’s “see and avoid” requirement. Systems such as the Traffic Alert and Collision Avoidance System (TCAS) and Mode S transponder satisfy part of the requirement for avoiding air traffic through cooperative technology. Cooperative technology incorporates the use of transponders to establish the position of participating air traffic to determine the possibility of a collision. No system or subsystem, however, is available to p rovide the “see and avoid” capability against non-cooperative aircraft. (Aircraft without a transponder based collision avoidance system) AFRL/SN has been commissioned to execute an Advanced Technology Demonstration of a sense and avoid (SAA) capability based on electro -optic sensors, innovative detection and tracking algorithms, and high performance data

Adaptive pattern-based image compression for ultra-low bandwidth weapon seeker image communication

The effectiveness of autonomous munitions systems can be enhanced by transmitting target images to a man-in-the-loop (MITL) as the system deploys. Based on the transmitted images, the MITL could change target priorities or conduct damage assessment in real-time. One impediment to this enhancement realization is the limited bandwidth of the system data-link. In this paper, an innovative pattern-based image compression technology is presented for enabling efficient image transmission over the ultra-low bandwidth system data link, while preserving sufficient details in the decompressed images for the MITL to perform the required assessments. Based on a pattern-driven image model, our technology exploits the structural discontinuities in the image by extracting and prioritizing edge segments with their geometric and intensity profiles. Contingent on the bit budget, only the most salient segments are encoded and transmitted, therefore achieving scalable bit-streams. Simulation results corroborate the technology efficiency and establish its subjective quality superiority over JPEG/JPEG2000 as well as feasibility for real-time implementation. Successful technology demonstrations were conducted using images from surrogate seekers in an aircraft and from a captive-carry test-bed system. The developed technology has potential applications in a broad range of network-enabled weapon systems.

An advanced missile warning processing suite

Effective missile warning and countermeasures remain an unfulfilled goal for the Air Force and others in the DOD community. To make the expectations a reality, newer sensors exhibiting the required sensitivity, field of regard, and spatial resolution are being developed and transitioned. The largest concern is in the first stage of a missile warning system: detection, in which all targets need to be detected with a high confidence and with very few false alarms. Typical fielded sensors are limited in their detection capability by either lack of sensitivity or by the presence of heavy background clutter, sun glints, and inherent sensor noise. Many threat environments include false alarm sources like burning fuels, flares, exploding ordinance, arc welders, and industrial emitters. Multicolor discrimination has been shown as one of the effective ways to improve the performance of missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in multiple demonstration and fielded systems. New exploitations of background and clutter spectral contents, coupled with advanced spatial and temporal filtering techniques, have resulted in a need to have a new baseline algorithm on which future processing advances may be judged against. This paper describes the AFRL Suite IIIc algorithm chain and its performance against long-range dim targets in clutter.

Near infrared missile warning testbed sensor

Multicolor discrimination is one of the most effective ways of improving the performance of infrared missile warning sensors, particularly for heavy clutter situations. A new tactical airborne multicolor missile warning testbed was developed and fielded as part of a continuing Air Force Research Laboratory (AFRL) initiative focusing on clutter and missile signature measurements for effective missile warning algorithms. The developed sensor test bed is a multi-camera system 1004x1004 FPA coupled with optimized spectral filters integrated with the optics; a reduced form factor microprocessor-based video data recording system operating at 48 Hz; and a real time field programmable gate array processor for algorithm and video data processing capable of 800B Multiply/Accumulates operations per second. A detailed radiometric calibration procedure was developed to overcome severe photon-limited operating conditions due to the sub-nanometer bandwidth of the spectral filters. This configuration allows the collection and real-time processing of temporally correlated, radiometrically calibrated video data in multiple spectral bands. The testbed was utilized to collect false alarm sources spectra and Man-Portable Air Defense System (MANPADS) signatures under a variety of atmospheric and solar illuminating conditions. Signatures of approximately 100 missiles have been recorded.

Multiple intruder tracking using a laser enhanced EO/IR Sense and Avoid system

Remotely Piloted Aircraft (RPA), otherwise known as Unmanned Aircraft Systems (UAS), need access to the National Airspace (NAS). For this to happen, a robust and reliable Sense and Avoid (SAA) technology that can simultaneously detect and track cooperative as well as non-cooperative intruders encountered in the NAS is required. To detect non-cooperative intruders, passive electro-optical (EO) and infra-red (IR) sensors are attractive from the size, weight and power (SWAP) considerations. As such they can be used even on small UAS. However, EO/IR sensors do not provide reliable range measurements. Another drawback of current EO/IR technology for detection of other air traffic is the unacceptable rate of false alarms generated due to clutter in images and small specks of clouds. The performance of the EO/IR sensors can be enhanced through the addition of laser ranging technology. A laser system can be cued by the EO/IR sensors to point towards the bearing of a suspected intruder. The laser returns can then be used to confirm the presence of the intruder and provide range information as well. In scenarios involving multiple intruders, gimbals/scanners may be employed to slew the laser from one intruder to another. This can take time and potentially limit the number of intruders that can be tracked. Intelligent sensor management and tracking algorithms can alleviate these problems to a good degree. In this paper, we address the problem of multiple-intruder tracking using a gimbaled laser system in conjunction with a passive EO/IR system. The main focus of the paper is on designing intelligent, effective and computationally efficient gimbal tasking algorithms. For realistic evaluation of system performance, we design and develop a software model of a generic EO-plus-laser system. We evaluate the performance of the system using Monte Carlo simulations based on encounters generated using the MIT Lincoln Laboratory encounter model of the National Airspace.

A spectral independent morphological adaptive classifier

Effective missile warning and countermeasures continue to be an unfulfilled goal for the Air Force and DOD community. To make the expectations a reality, sensors exhibiting the required sensitivity, field of regard, and spatial resolution are being pursued. The largest concern is in the first stage of a missile warning system, detection, in which all targets need to be detected with a high confidence and with very few false alarms. Typical sensors are limited in their detection capability by the presence of heavy background clutter, sun glints, and inherent sensor noise. Many threat environments include false alarm sources like burning fuels, flares, exploding ordinance, and industrial emitters. Multicolor discrimination is one of the effective ways of improving the performance of missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in multiple fielded systems. Utilization of the background and clutter spectral content, coupled with additional spatial and temporal filtering techniques, have resulted in a robust adaptive real-time algorithm to increase signal-to-clutter ratios against point targets. The algorithm is outlined and results against tactical data are summarized and compared in terms of computational cost expected to be implemented on a real-time field-programmable gate array (FPGA) processor.

Performance of SIMAC algorithm suite for tactical missile warning

Self protection of airborne assets has been important to the Air Force and DoD community for many years. The greatest threats to aircraft continue to be man portable air defense missiles and ground fire. AFRL has been pursuing a near-IR sensor approach that has shown to have better performance than midwave IR systems with much lower costs. SIMAC couples multiple spatial and temporal filtering techniques to provide the needed clutter suppression in the NIR missile warning systems. Results from flight tests will be discussed .

Empirical modeling and results of NIR clutter for tactical missile warning

A tactical airborne multicolor missile warning testbed was developed as part of an Air Force Research Laboratory (AFRL) initiative focusing on the development of sensors operating in the near infrared where commercially available silicon detectors can be used. The presentation will detail the new background and clutter data collections from ground and flight operations and results. It will outline the statistical analysis in both detection and guard bands to provide a basis for evaluation of sensor performance against missile and hostile fire threats. A general stochastic model for the NIR clutter will be presented and validity compared against flight data.